首页|Research from University of Georgia in the Area of Robotics Published (Robotic M ulti-Boll Cotton Harvester System Integration and Performance Evaluation)
Research from University of Georgia in the Area of Robotics Published (Robotic M ulti-Boll Cotton Harvester System Integration and Performance Evaluation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on robotics is now available. Accordi ng to news reporting from Athens, Georgia, by NewsRx journalists, research state d, "Several studies on robotic cotton harvesters have designed their end-effecto rs and harvesting algorithms based on the approach of harvesting a single cotton boll at a time." Financial supporters for this research include Cotton Incorporated. The news correspondents obtained a quote from the research from University of Ge orgia: "These robotic cotton harvesting systems often have slow harvesting times per boll due to limited computational speed and the extended time taken by actu ators to approach and retract for picking individual cotton bolls. This study mo dified the design of the previous version of the end-effector with the aim of im proving the picking ratio and picking time per boll. This study designed and fab ricated a pullback reel to pull the cotton plants backward while the rover harve sted and moved down the row. Additionally, a YOLOv4 cotton detection model and h ierarchical agglomerative clustering algorithm were implemented to detect cotton bolls and cluster them. A harvesting algorithm was then developed to harvest th e cotton bolls in clusters. The modified end-effector, pullback reel, vacuum con veying system, cotton detection model, clustering algorithm, and straight-line p ath planning algorithm were integrated into a small red rover, and both lab and field tests were conducted."
University of GeorgiaAthensGeorgiaUnited StatesNorth and Central AmericaAlgorithmsEmerging TechnologiesMac hine LearningRoboticsRobots
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